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Does loss diminish UF's season?
With the gloom now having had a chance to fully settle in over Gator Nation, many are wondering if one bad night, one bad loss diminishes what the Florida Gators accomplished over the course of an 11-1 regular season.
Florida coach Will Muschamp says it does not.
"No. We've had a great year," Muschamp said. "We're building something here. We're building a program. It's an unfortunate setback, and it's one game. We still won 11 games and we still did a lot of positive things this season.
"Obviously, this is a sour day and a sour note, and I apologize to our fans and the university. But we've had a great year and we're moving this thing forward at a rapid pace. I'm excited where we are. Very disappointed with the outcome, but very positive as we move forward."
The humbling 33-23 upset loss to No. 22 Louisville in the Sugar Bowl on Wednesday night certainly stalled the No. 4 Gators' late surge during this turnaround season, and puts the program in a bit of a funk heading into the long offseason with a defeat.
But does it damage or diminish the Gators' overall body of work in 2012?
Heading into the season, Florida was not considered a serious contender in the SEC in Muschamp's second year. Most picked the Gators (11-2) to lose three or four games and finish third in the Eastern Division behind Georgia and South Carolina.
Florida exceeded those expectations, defeating three top-10 teams and coming perhaps only a few plays away from winning the division and facing Alabama in the SEC Championship Game.
The Gators finished the regular season strong, downing Florida State 37-26 in Tallahassee with a performance that earned Florida a spot in a BCS bowl and gave the program all kinds of positive energy and momentum.
But the momentum hit the wall in Wednesday night's loss.
"I think we had good preparation," Muschamp said. "We just didn't play very well. Didn't coach very well.
"Our kids were excited about being at the Sugar Bowl in New Orleans, and they outcoached us and outplayed us."
Perhaps the biggest play of the game was the first — the Jeff Driskel pick-six that gave the fired-up Cardinals a 7-0 lead and set the tone for the night.
There were many other big plays that did not go Florida's way, including the failed onside kick to open the second half. Not only did the Gators fail to recover the kick, they were hit by two personal foul penalties that gave Louisville the ball on the UF 19. On the next play, Teddy Bridgewater threw a touchdown pass to Damian Copeland to increase the Louisville lead to 30-10.
"We felt it was there," Muschamp said. "We hit it too hard. We game-planned it and felt good about it. We wanted to steal a possession at the start of the second half. We had struggled defensively in the first half and felt like you try to gain some momentum in the game."
The Gators lost more momentum instead. It kind of played out like that throughout the game, with Driskel turning the ball over three times and UF hurting itself time and again with critical penalties.
So, instead of heading into the offseason with a great deal of momentum, the Gators go into it with a depressing loss that certainly will play a role in where UF starts the 2013 season in the polls.
"We did have a great year with a lot of wins," Driskel said. "But at the end of the day, we didn't come through (against Louisville) and we didn't make enough plays.
"It's unfortunate, but come Jan. 7, we're going to be refocused and ready to go for next season.
UF will move forward without two of its best junior defensive players. All-American safety Matt Elam and standout tackle Sharrif Floyd announced after the game that they were forgoing their senior seasons to enter the NFL Draft.
"I'm going into the draft," Elam said in the post-game locker room Wednesday night. "I had three great years. I did all I can for the team. I played my heart out. I feel like it's time to take care of the family."
Two other top juniors — tight end Jordan Reed and defensive tackle Dominique Easley — also are considering declaring for the draft.
While the players are heading back into the offseason strength and conditioning program, Muschamp and his coaching staff will try to close out what is expected to be one of the nation's best recruiting classes.
This turnaround season did not end on the positive note the Gators were hoping for and expecting. Now, it's time to regroup, self-evaluate and start thinking about moving forward.
Looking ahead, the Gators will have to replace four starters on offense (tackle Xavier Nixon, guard James Wilson, tailback Mike Gillislee and wide receiver Frankie Hammond Jr.) and six on defense (Floyd, Elam, tackle Omar Hunter, outside linebacker Lerentee McCray, middle linebacker Jon Bostic and safety Josh Evans). The Gators also will have to find a new kicker to replace Caleb Sturgis.
"I feel good about our football team coming back next season, I certainly do," Muschamp said.
Notes: The attendance of 54,178 is the Sugar Bowl's worst since 1939 and smallest ever for a BCS bowl. … Loucheiz Purifoy's injury was a thigh bruise, Muschamp said. "For those who care I'm fine," Purifoy wrote on his Twitter account. … Andre Debose extended his own school record for kick return touchdowns to four with his 100-yarder in the fourth quarter. He had a 99-yarder in last season's Gator Bowl, when he was chosen as the game's Most Valuable Player. … Sturgis broke Bobby Raymond's single-season school record (23) for field goals made with a 33-yarder in the second quarter. The record had stood since 1984. … With the two blocked kicks Wednesday, the Gators finished with six on the season (four field goals, one punt, one PAT) and UF has blocked 12 kicks in Muschamp's 26 games as a head coach. … Florida is now 20-20 all-time in bowls and 3-6 in the Sugar Bowl.
Contact Robbie Andreu at 352-374-5022 or email@example.com. Also check out Andreu's blog at Gatorsports.com.


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Innovative Policy: Zoning for Health
Posted by The Situationist Staff on September 29, 2007
We often hear about new and allegedly innovative approaches to implementing public policy. The key word, of course, is "innovative." By definition, it means the process of making improvements by introducing something new or — and particularly relevant to the following discussion — translating new ideas into tangible societal impact.
This year we've seen plenty of "innovative" approaches when it comes to public health. Some have attracted headlines. "Philadelphia follows New York in taking on trans-fat"; "Montgomery county declares war on partially hydrogenated oils in restaurants, supermarket bakeries, and delis."
The city of Los Angeles will soon contemplate its own new and likely controversial proposal for innovative public health policy: "health zoning plans" for fast-food. As Tami Abdollah of the Los Angeles Times details, LA's city council will be asked this fall to consider an up to two-year moratorium on new fast-food restaurants in South L.A., "a part of the city where fast food is at least as much a practicality as a preference."
NPR's All Things Considered outlines additional details on the proposed two-year moratorium. "In South Los Angeles, where 30 percent of adults are obese, activists and lawmakers are pointing to one possible cause: few dining-out choices except for fast food restaurants." According to NPR, this particular low-income area, much like other low-income urban areas across the country, offers few healthy food alternatives, even fewer grocery stores, and fast food chains may be found just a stone's throw away from each other.
Tami Abdollah describes the situation of many South L.A. residents this way.
* * *
Catalina Ayala, 23, who grew up in South Los Angeles, lives three blocks from a McDonald's and a slew of other fast-food restaurants, and eats fast food about four times a week.
"By the time I go home, it's already too late to cook food," said Ayala, who works at LAX.
On a recent afternoon, Ayala and her husband were at a McDonald's. Their 3-year-old son played in the indoor playground, which for some families serves as their children's park.
But her husband, a 23-year-old construction worker in South L.A., said he avoids fast food.
"It's not for me," he said. "Later on sometimes, your son is too fat, he eats too much."
That was one reason Terrah Cephas, 32, left South L.A. for the Valley about two years ago.
"It's fast food on every corner, but it's not enough wholesome restaurants," she said. "You literally have to be willing to drive to Long Beach or Santa Monica, or Inglewood."
That's if you have a car.
Many South L.A. residents are "almost a captive audience for these restaurants, unfortunately," Flynn said.
In South Los Angeles, 28% of people live in poverty, compared with 16.2% of the county, according to county figures.
South L.A. has lots of fast-food restaurants because these restaurants do well in areas where people might not want to spend $15 on lunch, said Dennis Lombardi, executive vice president of Foodservice Strategies at WD Partners, a restaurant consulting firm that works with Red Lobster, Jamba Juice and Fatburger, among others.
But there also may be missed opportunities: According to a 2005 market study contracted by the city, South L.A. loses more than $400 million annually in general merchandise, grocery and restaurant sales to outside areas.
"The community has suffered for decades by an assumption that attracting business of any type is good, and it's not true," Perry said.
* * *
In a situation where fast food is available twenty-four hours (and in abundance), it should not be surprising that an overweight population arises. Yet as discussed in Broken Scales: Obesity and Justice in America, a law review article by Situationist contributors Adam Benforado, Jon Hanson, and David Yosifon, "obesity is only a symptom of the problem." The "real problem" is the difficulty in recognizing and understanding "[roles] of unseen features in our environment and within us and too readily [attributing] responsibility and causation to the more obvious 'personal choices' of the obese." In essence, assigning obesity to personal choices alone and not discerning the relevant situational forces results in "misdiagnosing" the true problem. With obesity at an all-time high throughout the United States, 47 states are above 20% and fifteen years ago no state was above 15%, pressure to implement "innovative" plans (that work) will substantially increase.
Los Angeles' proposal enables a new term in policy, health zoning, which raises an important question: do policymakers have a responsibility to address public health problems generally attributed primarily to personal choice? More broadly, if people are moved largely by situation, and if situation is influenced by laws and policies, then should policymakers consider the situational consequences of their policies — intended and unintended.
For a collection of other posts on the situation of obesity, including Phil Zimbardo's most recent post, click here. For other posts on the regulation of food, click here.


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Wednesday, July 22, 2009
Brand New Food Show Ideas and a Casting Call
At the very least, this post should provide a few chuckles, but who knows -- maybe someone here will come up with the next big thing! By the way, any ideas you submit will be considered a gift, and will become my intellectual property -- to be used for good and/or evil as circumstances dictate.
Also, BNE is looking for a novice cook in the LA area to appear in a "sizzle reel." They need to be comfortable on camera, articulate and outgoing, and if they have a good reason for why they DON'T cook, well, even better. They will get a free cooking lesson from Chef John and best of all, their hard work in the kitchen will be rewarded with a super delicious and unforgettable meal. It will be a very fun afternoon!
If you are interested, please contact BNE at: firstname.lastname@example.com. Serious candidates only. Thanks!
Photo (c) Flickr user bormang2
42 comments:
Whenever I watch FoodTV, I always wish they had more shows that focus less on selling an image / personality than the food. I like Alton Brown because he talks food all the time. Most of the chef personalities on Foodtv seem to witter on for ages about stuff I really am not interested in. As you said before, it's about the food, and with that I don't think you can go wrong. :)
- July 22, 2009 at 4:09 PM
- Heidi / Savory Tv said...
Hey Chef John,
this may be boring or unoriginal, but I like spotlights on ingredients, such as "3 delicious appetizers featuring goat cheese", and tell us all about goat cheese during the show.
I also would love a show about certain things to keep in your kitchen at all times, and how to whip up appetizers using these ingredients for unexpected guests.
If the show will air in the fall or winter, slow cooker recipes seem to always be a hit. Chefs never seem to make those, but home cooks love them.
Bo-ring I know! But just my 1 cent :)
- July 22, 2009 at 4:45 PM
- Giovanna said...
Housewives Cookoff - who really has the best mac and cheese, stroganoff, lasagna, etc. I have always heard people say how much better their mom's cooking is but when I've had the chance to taste their mom's cooking, hmmm .. let's just say I think people can get used to bad cooking, especially if they grew up eating it. I once visited a friend of mine and their mother cooked for us, she NEVER even picked up the salt shaker! Ahhh!
It was a definite housewife horror! : )
Housewives please do not get offended.... just like everyone else out there, there are good, bad and really bad. Plus, I'm a housewife and half Italian and I still struggle to make a rockin' meal sometimes!
- July 22, 2009 at 7:15 PM
- nossi said...
One of the best shows on food network is Good Eats, and i think the reason why is because Alton explains everything. I would like to see a show similar to that, but not just focused on one thing (like chef brown does), rather whatever it is they are cooking, they take the time to explain what they are doing, and WHY they are doing what they do. More like a TV show based on "On food and Cooking" by McGee, or maybe "What einstein told his chef" by wolke..two books that i've read that really allowed me to appreciate cooking more
- July 22, 2009 at 7:28 PM
- Unknown said...
i want to see a show about food that takes hours and hours to cook, i am tired of fast tasting food, if that makes sense. travel somewhere, show how it's done, replicate in your kitchen.
- July 22, 2009 at 8:23 PM
- Chanelle said...
If I could have one thing in a cooking show it would be to have the recipe measurements on the show. So many shows now barely ever give you the measurements (you have to buy the book to get them) and it makes me really dislike the show.
That's why I like Good Eats so much, they show you the actual recipe.
- July 22, 2009 at 8:31 PM
- JGadFly said...
"By the way, any ideas you submit will be considered a gift, and will become my intellectual property -- to be used for good and/or evil as circumstances dictate."
Too, bad! I like your videos, I like your blog, but good ideas; come with a cost. You need to give credit, where credit is do. I will keep my ideas, for someone who appreciates the craft. I hosted/produced radio show for twelve years. I left, because they wanted me to sign an agreement, that said they could change the rules, as they saw fit. If you want to block me. feel free, to so.
- July 22, 2009 at 8:38 PM
"Im a chef, get me out of here." Enough said.
- July 22, 2009 at 8:47 PM
- Chef John said...
yes, good ideas come with a cost... that's why I'll take just average ones for free! Feel free to keep your (what I'm sure are pretty awesome) ideas to yourself.
btw, most culinary instruction comes with a cost, but not here! ;-)
- July 22, 2009 at 8:51 PM
After Chef John, my favorite Food Network show is Good Eats--Alton Brown. He TEACHES and educates about cooking from every aspect knowing that his audience may not know how to chiffonade herbs, which herbs to use, or how to select a knife or pan or even boil pasta. AB recognizes this and shows you the best methods and why. Not just history but techniques and WHY things are or happen the way they do. You want a winner of a show--plan to TEACH the methods and why's beyond the recipe--and challenge or give homework to get your audience involved. Watch Good eats for what his magic 'recipe' of success is IMO.
- July 22, 2009 at 11:29 PM
Oh wow, a class and a meal with chef John. That sounds fun :D
- July 22, 2009 at 11:38 PM
- milkshake said...
Chef, I just wrote you an e-mail - Best luck with everything.
- July 22, 2009 at 11:53 PM
I love Alton Brown - and I kind of like to know the why and how of cooking.
I also like shows where the chef goes to a person's home and helps them create a meal for a special occasion.
But what I'd really like is to see a chef come to my home, open my refrigerator on any day of the week - and make something special out of what I have on hand. You can't run to the store, you have to use the spices and equipment I have. Maybe that would help me look at the stuff I have with new eyes. I have a fridge full - but somehow the inspiration is kind of thin sometimes.
- July 23, 2009 at 12:55 AM
- Unknown said...
Another idea would be to have limited time for preparation by the chef.
Some viewers in the audience could choose, the last time, what food will be prepared. Or choose some of the ingredients.
Maybe some people passing by the road could choose.
Or there could be 2-3 possible recipes and viewers could vote with sms which will be prepared.
- July 23, 2009 at 1:33 AM
Other thoughts:
I'd also like to hear Chefs talk through how they decide on what goes on the plate to create a full meal.
Do you choose the protein first? How do you tie the sides together with the seasoning/garnishes to complement the main course?
Think out loud so we can hear your process about how to make a cohesive meal, 'cuz I can sometimes put together several individual items that aren't bad, but I'm not sure they 'go together'.
PLEASE do not use commercial appliances. Use what we use at home. We're at enough of a disadvantage without having your skill and education. That difference is just compounded when you use equipment we don't have.
There was a show on a long time ago - I think it was EARLY food network - where real people brought in several surprise ingredients and then assisted the chef in making a meal. I liked that show.
Maybe a show about how chefs cook at home? (Maybe there would have to be some creative liberties taken here, if dinner is a bowl of froot loops at 2am that really isn't really the concept I'm thinking of:)
- July 23, 2009 at 2:02 AM
Hey JGadFly, are you kidding??? He's just asking for some ideas. You want him to sign a profit sharing agreement before you tell him your ideas?? What a joke. How many free ideas have you found on his site? What nerve. You should sent him a check.
- July 23, 2009 at 2:15 AM
One of the many reasons I like chef John is he does not use gadgets. So I am sure we are safe as far as gadgets are concerned.
For someone to ask for $ for giving C.J and idea!! Ha! For everything that is available here for free!! Please!
Anywho that idea from Kelly on chef going to someone's home and cook something from what is available there, is a killer! Like that corn relish meal you made. I like that!
As for me I think you should show people how to use and take care of utensils from time to time. And food storage also.
And do bring Val to do chicken kiev. LOL.
- July 23, 2009 at 2:34 AM
- Unknown said...
Hello Chef John!
I know you hear this alot but, I really love your videos! I think I check your site about five times a week. :]
But anyway, I wanted to contribute an idea too. So, there could be a show with several chefs, each with a time limit, taking turns creating a dish, so like, the first guy has 10 minutes to work with what they have but after time's up, the next chef takes over.
Sounds boring huh? IE the first chef could just announce that they will make a soup and the other chefs finish his soup...BUT the twist is that each time the chefs rotate, a new ingrediant is introduced!
Try finishing a chicken soup with FIGS! >:]
- July 23, 2009 at 4:14 AM
- milkshake said...
cooking with whatever is available reminds me:
"And your dinner for the orchestra officials?"
"Haven't you ever had people
coming over and no time to shop? You have to make do with what's in the fridge, Clarice"
- July 23, 2009 at 4:26 AM
I'd like to see a show where it begins with the chef going to the market to buy the main ingredients (maybe teach the audience a bit about the ingredients), talks to the sellers/mongers, then goes home to cook the dish, explains some key points like you always do and takes a bite of the finished product.
- July 23, 2009 at 6:44 AM
- Amelie said...
I'm not in America and I can't watch the food network so I might be out of line but how about a show where you would visit other food bloggers and film with them one of their recording/inventing/cooking session. You could show their "behind the scene", their personnality and speciality and of course at least one or 2 recipes.
Good way to introduce people that diserve to be known, like you, to the world and show a recipe at the same time that would be pretty different every time.
- July 23, 2009 at 6:53 AM
- Pyrofish said...
I sent you an email from pyrofish, feel free to use it.
The gist, was to have a show where someone would volunteer their friend/significant other to go to the Chef John one on one cooking class. The twist is, the person who is volunteered doesn't know they were just sent to be schooled. Basically being told they can't cook.
It's up to Chef John to smooth things over, ask what they're experience level is, and start teaching them some things from there. It could be anything from selecting produce, and knife skills, to using the grill and/or the broiler. If the person is already proficient (according to the person who volunteered them), then you could teach them some more advanced techniques.
I don't think this could be done in someone's home though. If they don't know you're coming, they might be mad about the shape of their kitchen.
This would allow you to reach people who maybe don't watch cooking shows, but their friends or S/O's do. Possibly opening new audiences along the way. Plus you get the tension of the initial reveal, and by the end of the show, they're happy and making good food.
- July 23, 2009 at 9:36 AM
How about a theme for one show where you show and explain how to get everything ready at the correct time. I find myself having problems with that sometimes. Especially when serving three course menu, the main course burns when I'm eating the entré or then there is 30 min break between those :)
- July 23, 2009 at 10:28 AM
- Chase Saunders said...
JGadfly thinks ideas are worth something. I would be willing to wager he has never sold an idea nor patented anything. In my experience money guys will laugh, and then leave, if you ask them to pay for an idea or even sign a confidentiality agreement before telling to them. It's the ability to generate and execute ideas that people will pay for, not ideas themselves. As Howard Aiken said, "Don't worry about people stealing your ideas. If your ideas are any good, you'll have to ram them down people's throats."
All that being said, here is mine. Food costs are going up and up and all signs point to that trend continuing. I imagine most people are going to have to make rather significant changes in their diet. While "frugal cooking" books about, it's harder to find an approach that balances frugality with other values.
- July 23, 2009 at 11:04 AM
Nice quote, Chase!
Chef, I have no doubt that you'll find the show that works for you, and I can't wait. Good Luck.
Maybe, a "What If..." show?
I'd like to see What If Julia Child got into professional wrestling instead. What a visual! The Iron Sheik looking across the ring at a 6'10 Julia Child, with her apron swinging back and forth... She'd destroy him! Her trademark line would've been, "Bon Appetite, &@#$%$#!"
Man, I'm excited just thinking about it!... I gotta sit down...
Just a thought.
- July 23, 2009 at 5:35 PM
Aside from the fancy visual filters that enrich the video on the food network and make the food pop for the camera in color and texture.... (especially in HD)...
There are a lot of shows that are more of "This Food's Greatest Hits"... this or "(Add Food network Personality) Version of Classic "This"" ...
I would like to see more exotic cooking or more specifically cooking that's "current" new recipes, new flavor combinations, new ways of garnishing/presentations, and new food concepts that are out there waiting to be discovered.....
I think the cutting edge food that's coming out in modern up-scale restaurants and down home cooking that's being reinvented is very entertaining simply because it capitalizes on the adventurous aspect that food has that not only inspires people to cook more but allows them to take risks with confidence in their own cooking...
I think the food network junkies are tired of reviewing the basics over and over and can find it a bit redundant...... They need newer and more exciting cooking...content that makes it entertaining for Professional Chef's and advanced Home Chef's....(not too mention blowing the mind of beginners :P)
Because the content on Food Network now (in my opinion granted) is geared towards getting new audience members so it's at a beginner and intermediate viewer level......So an Advanced and Professional Level needs to come along to Keep existing food junkies who've been long time viewers who need something more.....
meh...we'll see....
Thanks C.J. : D
P.S.- You could always title your show.... "Good Lookin' Simple Cookin'" : P
- July 24, 2009 at 12:14 PM
- averagebetty said...
What about a late night munchies kind of show? You meet people at clubs on their way out the door. You offer to whip them up some appetizers with whatever you find in their home pantry? Champagne and white bean crostini could come of it... Can't imagine where I got that idea - it just came to me ;)
I want to be on your show, Chef John! You are the best <3
- July 24, 2009 at 6:50 PM
- Chef John said...
thanks to everyone for all the great ideas!! (except gadfly)
betty, that's a great idea, but this has to play in LA... that sounds like something that would be better for a smaller town, like say, Aspen? ;-)
- July 25, 2009 at 12:53 AM
Everyone enjoys a great meal out, but it can be too expensive for many of us, especially prohibitive at the top chef's restaurants, and so maybe every so often you could give a demonstration on how to replicate signature dishes from renowned chefs. And gee, if the producers want to make it authentic they can fly you to some of these establishments so you can get firsthand impressions.
- July 25, 2009 at 3:45 AM
I'd like to see your show work with high school age kids, to help them learn some cooking techniques. Many high schoolers are latchkey kids and have to fend for themselves at meal time, and more than you can imagine, many teens would like to learn cooking technique. Schools no longer teach classes that assist with life skills or possible careers like wood shop, automotive shops, sewing and cooking in home ec, so be the Alice Waters of reality tv and give our poor sagging public education a boost in the right direction.
- July 25, 2009 at 2:20 PM
- powerplantop said...
"to be used for good and/or evil as circumstances dictate."
I have an idea that could be used for evil and it will work in LA. Show us how to make street food at home. How do those guys in the taco trucks make them so good? How do you make good Pho? A great chili dog? Fish taco?
- July 25, 2009 at 4:54 PM
Pretend you have nasal congestion and do that 'hey, how're you doing?' sexy voice you did on ciabatta bread!!! Hilarious!
- July 27, 2009 at 8:21 AM
- Chez US said...
I have a very novice cook that would be great on TV but he does not live in LAX .... he needs to learn to cook, Chef John!
- July 27, 2009 at 10:58 AM
Dear Chef John,
I am living in Austria and have no idea whatsoever what American food shows are like so please don't be mad if you already got my suggestion over there.
My idea:
You know the show where a woman has to choose a man for a date by asking him stupid questions? Take the exact same idea but instead of mindless glibberish the girl (must?) degust what the 3 guys cooked for her in the last 30 minutes. As far as I know you Americans like if there is plenty of action, so the camera would follow the three (amateur?) cooks at the same time, 24 style, and they would briefly explain what they are doing but the real deal would be the audience guessing which meal scores... (of course the detailed recipies could be downloaded on the net, for all the singles out there, afterwards)
Well, it's just a warmed up idea of already existing ingredients, but isn't that how the creative industry works nowadays? I totally gift this idea to you, hope it will be the next Oprah and net you millions, so you can continue to enjoy us with your wonderful blog for years to come.
Best wishes
- July 27, 2009 at 7:51 PM
Just thought of something:
I understand it's near-impossible with "corporate" in the way, but a foodie Consumer Reports of sorts would be great. Consider that the "Best of" San Fran, Boston, etc. are always the most popular issues of the year for any publication.
Blind tastings, product ratings... people really love that stuff.
Scott - Boston
- July 27, 2009 at 9:28 PM
I agree with alot of the other comments, Good Eats is the best show on Food Network, in my opinion. Also I would LOVE to not have to go online or buy a book (that will just get destroyed in my kitchen with all the sloppy cooking I do)to get their recipes. So I liked the prev. Idea on posting the ingred/ amounts on the show. I loved the FN for a long time for almost 8+ years now. However I find it too glossy and glam. I was kinda pissed about that stupid "next food network star" show. Really? The next star? Lame.
I miss the show who's name escapes me but was just about desserts. The chef had her own bakery and was making her goods on her segment.
~I started watching food network because it was supposed to be about food, and how to cook it. I also started watching because I missed my pbs shows from childhood such as- Yan Can Cook, Frugal Gourmet, and the French chef Jacques who made his French pastries and desserts.I want that kind of show back on tv.
~I think that the reason why youtube and foody blogs have become so pop. is because ppl are tired of FN making food glitzy and commercial. SO this isn't an idea obv. but my suggestion is just do what you do best. Its worked thus far hasn't it? You don't need a gimmick or some fancy idea, just cook, make all your yummy recipes you have on here. I know I'll be watching :)
- July 29, 2009 at 5:57 PM
- Tyler said...
i've always thought a show with so-so amature teenagers competing would be sort of interesting ...
i've also always thought i could pwn one of those shows lol!
meh, i suppose it could be interesting TV, and who knows, maybe a diamond in the ruff could be found :O
- July 31, 2009 at 7:14 PM
- Reckless said...
I am with a lot of the other commentors here in my feeling that the Food Network has really strayed away from food education and focused more on cute personalities and "quick" or "cheap" meals. With the exception of Alton Brown, there are very few shows from which, even as an amature/hobbiest chef, I am able to learn anything new. A lot of my friends and I have begun to turn away from Food Network because the new shows just don't teach very much.
I think it would be great to have a show that taught theory, technique, etc. in a way similar to the methods used in cullinary school. I would love shows that were dedicated to knife skills, whisking techniques, strategies for serving multi-course meals using one oven/stovetop.
Btw, love your site!!!
- August 12, 2009 at 10:10 AM
- Unknown said...
A good cooking show would b with a younger crowd. The idea of kids who love to cook and is still learning. They should be given hints on how to cook things or study ways to make something. The winner should get something like a scholarship or a trips different foreign countries to learn different cuisines. We should give reward them bigger in what they want to do and not always just money but to explore the world. You can even have a show with amateur cooks make them better and the winner gets to cook and learn by cooking under a better and well skilled chef. And on these shows the judges are exaggerating when they critique the cooks.
- January 4, 2010 at 11:19 PM
- Fran said...
There are a lot of shows on Food Network where people who are already chefs compete, and now there is a show called "Worst Cooks" in which people who are terrible cooks are taught by two celebrity chefs how to cook. What about those of us in the middle? People who watch Food Network and actually CAN cook, and may aspire to be chefs. I'd love to see (read: be a competitor on) a show for people who can cook, or think they can cook, and want to become chefs. Instead of a cash prize, the grand prize should be a scholarship to attend a culinary school.
- January 8, 2011 at 3:55 PM
This is an old post and may not be relevant anymore.
This is not "my idea." Instead I'm blending ideas already suggested in this post because these are so good!
Heidi/Savory TV has a good idea about exploring an ingredient with several recipes (but not like Robin does in cooking for the whole week – icky stuff half the time). And Heidi's idea about kitchen essential ingredients is excellent be the rest of us don't have things like white truffles or quail eggs handy.
Anonymous asks not to use commercial appliances, and I agree there too. In fact, that's one reason why Chef John recipes are so simple (and sophisticated) because mostly you use a bowl and spatula. Where's that Vitamix machine and the Kicthenaid with the dough hooks? ;)
Amelie suggested cooking with food bloggers…so brilliant. Just imagine the variety – vegan, Paleo, cupcakes….and the countries represented – Spain, Mexico, France, etc. (right here in the U.S.!)
So there you go – food bloggers exploring what to do with an ingredient/recipe/meal (Tamales at Christmas? Yorkshire pudding? You don't say!) using relatively ordinary equipment and ingredients. How about Chef John presenting a simple and simply delicious recipe using an ingredient, and then visiting a blogger to see a different treatment of the ingredient?
These ideas blended together appeal to me because that's what we do on the internet…we drift around from blog to blog looking for the recipe and technique to candy orange peels that we are willing and brave enough to try. Bring THAT to TV.
- July 28, 2012 at 2:20 AM
- Unknown said...
How about a show called Field to Table (NOT Farm to Table). I'm a female hunter who loves to cook wild game. Even women who don't hunt have husbands that bring home venison, duck, pheasant, etc. that sits in the freezer and goes to waste because no one knows how to cook it. The show would start in the field during the hunt (or in the stream) and then finish in the kitchen. Great idea, right?
- October 21, 2018 at 6:07 PM


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NLopt Algorithms
NLopt includes implementations of a number of different optimization algorithms. These algorithms are listed below, including links to the original source code (if any) and citations to the relevant articles in the literature (see Citing NLopt).
Even where I found available free/open-source code for the various algorithms, I modified the code at least slightly (and in some cases noted below, substantially) for inclusion into NLopt. I apologize in advance to the authors for any new bugs I may have inadvertantly introduced into their code.
Each algorithm in NLopt is identified by a named constant, which is passed to the NLopt routines in the various languages in order to select a particular algorithm. These constants are mostly of the form
NLOPT_{G,L}{N,D}_xxxx, where
L denotes global/local optimization and
D denotes derivative-free/gradient-based algorithms, respectively.
For example, the
NLOPT_LN_COBYLA constant refers to the COBYLA algorithm (described below), which is a local (
L) derivative-free (
N) optimization algorithm.
Two exceptions are the MLSL and augmented Lagrangian algorithms, denoted by
NLOPT_G_MLSL and
NLOPT_AUGLAG, since whether or not they use derivatives (and whether or not they are global, in
AUGLAG's case) is determined by what subsidiary optimization algorithm is specified.
Many of the algorithms have several variants, which are grouped together below.
Comparing algorithms
For any given optimization problem, it is a good idea to compare several of the available algorithms that are applicable to that problem—in general, one often finds that the "best" algorithm strongly depends upon the problem at hand.
However, comparing algorithms requires a little bit of care because the function-value/parameter tolerance tests are not all implemented in exactly the same way for different algorithms. So, for example, the same fractional 10−4 tolerance on the function value might produce a much more accurate minimum in one algorithm compared to another, and matching them might require some experimentation with the tolerances.
Instead, a more fair and reliable way to compare two different algorithms is to run one until the function value is converged to some value fA, and then run the second algorithm with the minf_max termination test set to minf_max=fA. That is, ask how long it takes for the two algorithms to reach the same function value.
Better yet, run some algorithm for a really long time until the minimum fM is located to high precision. Then run the different algorithms you want to compare with the termination test: minf_max=fM+Δf. That is, ask how long it takes for the different algorithms to obtain the minimum to within an absolute tolerance Δf, for some Δf. (This is totally different from using the ftol_abs termination test, because the latter uses only a crude estimate of the error in the function values, and moreover the estimate varies between algorithms.)
Global optimization
All of the global-optimization algorithms currently require you to specify bound constraints on all the optimization parameters. Of these algorithms, only ISRES, AGS, and ORIG_DIRECT support nonlinear inequality constraints, and only ISRES supports nonlinear equality constraints. (However, any of them can be applied to nonlinearly constrained problems by combining them with the augmented Lagrangian method below.)
Something you should consider is that, after running the global optimization, it is often worthwhile to then use the global optimum as a starting point for a local optimization to "polish" the optimum to a greater accuracy. (Many of the global optimization algorithms devote more effort to searching the global parameter space than in finding the precise position of the local optimum accurately.)
DIRECT and DIRECT-L
DIRECT is the DIviding RECTangles algorithm for global optimization, described in:
- D. R. Jones, C. D. Perttunen, and B. E. Stuckmann, "Lipschitzian optimization without the lipschitz constant," J. Optimization Theory and Applications, vol. 79, p. 157 (1993).
and DIRECT-L is the "locally biased" variant proposed by:
- J. M. Gablonsky and C. T. Kelley, "A locally-biased form of the DIRECT algorithm," J. Global Optimization, vol. 21 (1), p. 27-37 (2001).
These are deterministic-search algorithms based on systematic division of the search domain into smaller and smaller hyperrectangles. The Gablonsky version makes the algorithm "more biased towards local search" so that it is more efficient for functions without too many local minima. NLopt contains several implementations of both of these algorithms. I would tend to try
NLOPT_GN_DIRECT_L first; YMMV.
First, it contains a from-scratch re-implementation of both algorithms, specified by the constants
NLOPT_GN_DIRECT and
NLOPT_GN_DIRECT_L, respectively.
Second, there is a slightly randomized variant of DIRECT-L, specified by
NLOPT_GN_DIRECT_L_RAND, which uses some randomization to help decide which dimension to halve next in the case of near-ties.
The DIRECT and DIRECT-L algorithms start by rescaling the bound constraints to a hypercube, which gives all dimensions equal weight in the search procedure. If your dimensions do not have equal weight, e.g. if you have a "long and skinny" search space and your function varies at about the same speed in all directions, it may be better to use unscaled variants of these algorthms, which are specified as
NLOPT_GN_DIRECT_L_NOSCAL, and
NLOPT_GN_DIRECT_L_RAND_NOSCAL, respectively. However, the unscaled variations make the most sense (if any) with the original DIRECT algorithm, since the design of DIRECT-L to some extent relies on the search region being a hypercube (which causes the subdivided hyperrectangles to have only a small set of side lengths).
Finally, NLopt also includes separate implementations based on the original Fortran code by Gablonsky et al. (1998-2001), which are specified as
NLOPT_GN_ORIG_DIRECT and
NLOPT_GN_ORIG_DIRECT_L. These implementations have a number of hard-coded limitations on things like the number of function evaluations; I removed several of these limitations, but some remain. On the other hand, there seem to be slight differences between these implementations and mine; most of the time, the performance is roughly similar, but occasionally Gablonsky's implementation will do significantly better than mine or vice versa.
Most of the above algorithms only handle bound constraints, and in fact require finite bound constraints (they are not applicable to unconstrained problems). They do not handle arbitrary nonlinear constraints. However, the
ORIG versions by Gablonsky et al. include some support for arbitrary nonlinear inequality constraints.
Controlled Random Search (CRS) with local mutation
My implementation of the "controlled random search" (CRS) algorithm (in particular, the CRS2 variant) with the "local mutation" modification, as defined by:
- P. Kaelo and M. M. Ali, "Some variants of the controlled random search algorithm for global optimization," J. Optim. Theory Appl. 130 (2), 253-264 (2006).
The original CRS2 algorithm was described by:
- W. L. Price, "A controlled random search procedure for global optimization," in Towards Global Optimization 2, p. 71-84 edited by L. C. W. Dixon and G. P. Szego (North-Holland Press, Amsterdam, 1978).
- W. L. Price, "Global optimization by controlled random search," J. Optim. Theory Appl. 40 (3), p. 333-348 (1983).
The CRS algorithms are sometimes compared to genetic algorithms, in that they start with a random "population" of points, and randomly "evolve" these points by heuristic rules. In this case, the "evolution" somewhat resembles a randomized Nelder-Mead algorithm. The published results for CRS seem to be largely empirical; limited analytical results about its convergence were derived in:
- Eligius M. T. Hendrix, P. M. Ortigosa, and I. García, "On success rates for controlled random search," J. Global Optim. 21, p. 239-263 (2001).
The initial population size for CRS defaults to 10×(n+1) in n dimensions, but this can be changed with the nlopt_set_population function; the initial population must be at least n+1.
Only bound-constrained problems are supported by this algorithm.
CRS2 with local mutation is specified in NLopt as
MLSL (Multi-Level Single-Linkage)
This is my implementation of the "Multi-Level Single-Linkage" (MLSL) algorithm for global optimization by a sequence of local optimizations from random starting points, proposed by:
- A. H. G. Rinnooy Kan and G. T. Timmer, "Stochastic global optimization methods," Mathematical Programming, vol. 39, p. 27-78 (1987). (Actually 2 papers — part I: clustering methods, p. 27, then part II: multilevel methods, p. 57.)
We also include a modification of MLSL use a Sobol' low-discrepancy sequence (LDS) instead of pseudorandom numbers, which was argued to improve the convergence rate by:
- Sergei Kucherenko and Yury Sytsko, "Application of deterministic low-discrepancy sequences in global optimization," Computational Optimization and Applications, vol. 30, p. 297-318 (2005).
In either case, MLSL is a "multistart" algorithm: it works by doing a sequence of local optimizations (using some other local optimization algorithm) from random or low-discrepancy starting points. MLSL is distinguished, however by a "clustering" heuristic that helps it to avoid repeated searches of the same local optima, and has some theoretical guarantees of finding all local optima in a finite number of local minimizations.
The local-search portion of MLSL can use any of the other algorithms in NLopt, and in particular can use either gradient-based (
D) or derivative-free algorithms (
N) The local search uses the derivative/nonderivative algorithm set by
LDS-based MLSL with is specified as
NLOPT_G_MLSL_LDS, while the original non-LDS original MLSL (using pseudo-random numbers, currently via the Mersenne twister algorithm) is indicated by
NLOPT_G_MLSL. In both cases, you must specify the local optimization algorithm (which can be gradient-based or derivative-free) via
Note: If you do not set a stopping tolerance for your local-optimization algorithm, MLSL defaults to ftol_rel=10−15 and xtol_rel=10−7 for the local searches. Note that it is perfectly reasonable to set a relatively large tolerance for these local searches, run MLSL, and then at the end run another local optimization with a lower tolerance, using the MLSL result as a starting point, to "polish off" the optimum to high precision.
By default, each iteration of MLSL samples 4 random new trial points, but this can be changed with the nlopt_set_population function.
Only bound-constrained problems are supported by this algorithm.
This is an algorithm adapted from the code downloaded from
by Madsen et al. StoGO is a global optimization algorithm that works by systematically dividing the search space (which must be bound-constrained) into smaller hyper-rectangles via a branch-and-bound technique, and searching them by a gradient-based local-search algorithm (a BFGS variant), optionally including some randomness (hence the "Sto", which stands for "stochastic" I believe).
StoGO is written in C++, which means that it is only included when you compile the C++ algorithms enabled, in which case (on Unix) you must link to
-lnlopt_cxx instead of
StoGO is specified within NLopt by
NLOPT_GD_STOGO, or
NLOPT_GD_STOGO_RAND for the randomized variant.
Some references on StoGO are:
- S. Gudmundsson, "Parallel Global Optimization," M.Sc. Thesis, IMM, Technical University of Denmark, 1998.
- K. Madsen, S. Zertchaninov, and A. Zilinskas, "Global Optimization using Branch-and-Bound," unpublished (1998). A preprint of this paper is included in the
stogosubdirectory of NLopt as
- S. Zertchaninov and K. Madsen, "A C++ Programme for Global Optimization," IMM-REP-1998-04, Department of Mathematical Modelling, Technical University of Denmark, DK-2800 Lyngby, Denmark, 1998. A copy of this report is included in the
stogosubdirectory of NLopt as
Only bound-constrained problems are supported by this algorithm.
This algorithm adapted from this repo. AGS can handle arbitrary objectives and nonlinear inequality constraints. Also bound constraints are required for this method. To guarantee convergence, objectives and constraints should satisfy the Lipschitz condition on the specified hyperrectangle. AGS is derivative-free and employs the Hilbert curve to reduce the source problem to the univariate one. The algorithm divides the univariate space into intervals, generating new points by using posterior probabilities. On each trial AGS tries to evaluate the constraints consequently one by one. If some constraint is violated at this point, the next ones won't be evaluated. If all constraints are preserved, i.e. the trial point is feasible, AGS will evaluate the objective. Thus, some of constraints (except the first one) and objective can be partially undefined inside the search hyperrectangle. Current implementation of AGS doesn't support vector constraints.
Limitations of the machine arithmetic don't allow to build a tight approximation for Hilbert when the space dimension is greater than 5, so this implementation of AGS is restricted in that sense. It supports up to 10 dimensions, but the method can stop early in case of 6 and more ones.
AGS, like StoGO, is written in C++, but it requires C++11. If the library is built with C++ and compiler supports C++11, AGS will be built too.
AGS is specified within NLopt by
NLOPT_GN_AGS. Additional parameters of AGS which are not adjustable from the common NLOpt interface are declared and described in
ags.h. Also an example of solving a constrained problem is given in the AGS source folder.
Yaroslav D. Sergeyev, Dmitri L. Markin: An algorithm for solving global optimization problems with nonlinear constraints, Journal of Global Optimization, 7(4), pp 407–419, 1995
Strongin R.G., Sergeyev Ya.D., 2000. Global optimization with non-convex constraints. Sequential and parallel algorithms. Kluwer Academic Publishers, Dordrecht.
Gergel V. and Lebedev I.: Heterogeneous Parallel Computations for Solving Global Optimization Problems. Proc. Comput. Science 66, pp. 53–62 (2015)
Implementation of AGS for constrained multi-objective problems.
ISRES (Improved Stochastic Ranking Evolution Strategy)
This is my implementation of the "Improved Stochastic Ranking Evolution Strategy" (ISRES) algorithm for nonlinearly-constrained global optimization (or at least semi-global; although it has heuristics to escape local optima, I'm not aware of a convergence proof), based on the method described in:
- Thomas Philip Runarsson and Xin Yao, "Search biases in constrained evolutionary optimization," IEEE Trans. on Systems, Man, and Cybernetics Part C: Applications and Reviews, vol. 35 (no. 2), pp. 233-243 (2005).
It is a refinement of an earlier method described in:
- Thomas P. Runarsson and Xin Yao, "Stochastic ranking for constrained evolutionary optimization," IEEE Trans. Evolutionary Computation, vol. 4 (no. 3), pp. 284-294 (2000).
This is an independent implementation by S. G. Johnson (2009) based on the papers above. Runarsson also has his own Matlab implemention available from his web page here.
The evolution strategy is based on a combination of a mutation rule (with a log-normal step-size update and exponential smoothing) and differential variation (a Nelder–Mead-like update rule). The fitness ranking is simply via the objective function for problems without nonlinear constraints, but when nonlinear constraints are included the stochastic ranking proposed by Runarsson and Yao is employed. The population size for ISRES defaults to 20×(n+1) in n dimensions, but this can be changed with the nlopt_set_population function.
This method supports arbitrary nonlinear inequality and equality constraints in addition to the bound constraints, and is specified within NLopt as
ESCH (evolutionary algorithm)
This is a modified Evolutionary Algorithm for global optimization, developed by Carlos Henrique da Silva Santos's and described in the following paper and Ph.D thesis:
- C. H. da Silva Santos, M. S. Gonçalves, and H. E. Hernandez-Figueroa, "Designing Novel Photonic Devices by Bio-Inspired Computing," IEEE Photonics Technology Letters 22 (15), pp. 1177–1179 (2010).
- C. H. da Silva Santos, "Parallel and Bio-Inspired Computing Applied to Analyze Microwave and Photonic Metamaterial Strucutures," Ph.D. thesis, University of Campinas, (2010).
The algorithm is adapted from ideas described in:
- H.-G. Beyer and H.-P. Schwefel, "Evolution Strategies: A Comprehensive Introduction," Journal Natural Computing, 1 (1), pp. 3–52 (2002_.
- Ingo Rechenberg, "Evolutionsstrategie – Optimierung technischer Systeme nach Prinzipien der biologischen Evolution," Ph.D. thesis (1971), Reprinted by Fromman-Holzboog (1973).
The method supports bound constraints only (no nonlinear constraints), and is specified within NLopt as
Local derivative-free optimization
Of these algorithms, only COBYLA currently supports arbitrary nonlinear inequality and equality constraints; the rest of them support bound-constrained or unconstrained problems only. (However, any of them can be applied to nonlinearly constrained problems by combining them with the augmented Lagrangian method below.)
A unique consideration when using local derivative-free algorithms is that the optimizer must somehow decide on an initial step size. By default, NLopt chooses this initial step size heuristically, but this may not always be the best choice. If you run into trouble, you can modify the initial step size, as described in the NLopt reference.
COBYLA (Constrained Optimization BY Linear Approximations)
This is a derivative of Powell's implementation of the COBYLA (Constrained Optimization BY Linear Approximations) algorithm for derivative-free optimization with nonlinear inequality and equality constraints, by M. J. D. Powell, described in:
- M. J. D. Powell, "A direct search optimization method that models the objective and constraint functions by linear interpolation," in Advances in Optimization and Numerical Analysis, eds. S. Gomez and J.-P. Hennart (Kluwer Academic: Dordrecht, 1994), p. 51-67.
and reviewed in:
- M. J. D. Powell, "Direct search algorithms for optimization calculations," Acta Numerica 7, 287-336 (1998).
It constructs successive linear approximations of the objective function and constraints via a simplex of n+1 points (in n dimensions), and optimizes these approximations in a trust region at each step.
The original code itself was written in Fortran by Powell and was converted to C in 2004 by Jean-Sebastien Roy (email@example.com) for the SciPy project. The version in NLopt was based on Roy's C version, downloaded from:
NLopt's version is slightly modified in a few ways. First, we incorporated all of the NLopt termination criteria. Second, we added explicit support for bound constraints (although the original COBYLA could handle bound constraints as linear constraints, it would sometimes take a step that violated the bound constraints). Third, we allow
COBYLA to increase the trust-region radius if the predicted improvement was approximately right and the simplex is OK, following a suggestion in the SAS manual for PROC NLP that seems to improve convergence speed. Fourth, we pseudo-randomize simplex steps in COBYLA algorithm, improving robustness by avoiding accidentally taking steps that don't improve conditioning (which seems to happen sometimes with active bound constraints); the algorithm remains deterministic (a deterministic seed is used), however. Also, we support unequal initial-step sizes in the different parameters (by the simple expedient of internally rescaling the parameters proportional to the initial steps), which is important when different parameters have very different scales.
(The underlying COBYLA code only supports inequality constraints. Equality constraints are automatically transformed into pairs of inequality constraints, which in the case of this algorithm seems not to cause problems.)
It is specified within NLopt as
This is an algorithm derived from the BOBYQA subroutine of M. J. D. Powell, converted to C and modified for the NLopt stopping criteria. BOBYQA performs derivative-free bound-constrained optimization using an iteratively constructed quadratic approximation for the objective function. See:
- M. J. D. Powell, "The BOBYQA algorithm for bound constrained optimization without derivatives," Department of Applied Mathematics and Theoretical Physics, Cambridge England, technical report NA2009/06 (2009).
(Because BOBYQA constructs a quadratic approximation of the objective, it may perform poorly for objective functions that are not twice-differentiable.)
The NLopt BOBYQA interface supports unequal initial-step sizes in the different parameters (by the simple expedient of internally rescaling the parameters proportional to the initial steps), which is important when different parameters have very different scales.
This algorithm, specified in NLopt as
NLOPT_LN_BOBYQA, largely supersedes the NEWUOA algorithm below, which is an earlier version of the same idea by Powell.
NEWUOA + bound constraints
This is an algorithm derived from the NEWUOA subroutine of M. J. D. Powell, converted to C and modified for the NLopt stopping criteria. I also modified the code to include a variant, NEWUOA-bound, that permits efficient handling of bound constraints. This algorithm is largely superseded by BOBYQA (above).
The original NEWUOA performs derivative-free unconstrained optimization using an iteratively constructed quadratic approximation for the objective function. See:
- M. J. D. Powell, "The NEWUOA software for unconstrained optimization without derivatives," Proc. 40th Workshop on Large Scale Nonlinear Optimization (Erice, Italy, 2004).
(Because NEWUOA constructs a quadratic approximation of the objective, it may perform poorly for objective functions that are not twice-differentiable.)
The original algorithm is specified in NLopt as
NLOPT_LN_NEWUOA, and only supports unconstrained problems. For bound constraints, my variant is specified as
In the original NEWUOA algorithm, Powell solved the quadratic subproblems (in routines TRSAPP and BIGLAG) in a spherical trust region via a truncated conjugate-gradient algorithm. In my bound-constrained variant, we use the MMA algorithm for these subproblems to solve them with both bound constraints and a spherical trust region. In principle, we should also change the BIGDEN subroutine in a similar way (since BIGDEN also approximately solves a trust-region subproblem), but instead I just truncated its result to the bounds (which probably gives suboptimal convergence, but BIGDEN is called only very rarely in practice).
Shortly after my addition of bound constraints to NEWUOA, Powell released his own version of NEWUOA modified for bound constraints as well as some numerical-stability and convergence enhancements, called BOBYQA. NLopt now incorporates BOBYQA as well, and it seems to largely supersede NEWUOA.
Note: NEWUOA requires the dimension n of the parameter space to be ≥ 2, i.e. the implementation does not handle one-dimensional optimization problems.
PRAXIS (PRincipal AXIS)
"PRAXIS" gradient-free local optimization via the "principal-axis method" of Richard Brent, based on a C translation of Fortran code downloaded from Netlib:
The original Fortran code was written by Richard Brent and made available by the Stanford Linear Accelerator Center, dated 3/1/73. The appropriate reference seems to be:
- Richard Brent, Algorithms for Minimization without Derivatives (Prentice-Hall, 1972). (Reprinted by Dover, 2002.)
Specified in NLopt as
This algorithm was originally designed for unconstrained optimization. In NLopt, bound constraints are "implemented" in PRAXIS by the simple expedient of returning infinity (Inf) when the constraints are violated (this is done automatically—you don't have to do this in your own function). This seems to work, more-or-less, but appears to slow convergence significantly. If you have bound constraints, you are probably better off using COBYLA or BOBYQA.
Nelder-Mead Simplex
My implementation of almost the original Nelder-Mead simplex algorithm (specified in NLopt as
NLOPT_LN_NELDERMEAD), as described in:
- J. A. Nelder and R. Mead, "A simplex method for function minimization," The Computer Journal 7, p. 308-313 (1965).
This method is simple and has demonstrated enduring popularity, despite the later discovery that it fails to converge at all for some functions (and examples may be constructed in which it converges to point that is not a local minimum). Anecdotal evidence suggests that it often performs well even for noisy and/or discontinuous objective functions. I would tend to recommend the Subplex method (below) instead, however.
The main change compared to the 1965 paper is that I implemented explicit support for bound constraints, using essentially the method proposed in:
- M. J. Box, "A new method of constrained optimization and a comparison with other methods," Computer J. 8 (1), 42-52 (1965).
and later reviewed in:
- J. A. Richardson and J. L. Kuester, "The complex method for constrained optimization," Commun. ACM 16 (8), 487-489 (1973).
Whenever a new point would lie outside the bound constraints, Box advocates moving it "just inside" the constraints by some fixed "small" distance of 10−8 or so. I couldn't see any advantage to using a fixed distance inside the constraints, especially if the optimum is on the constraint, so instead I move the point exactly onto the constraint in that case. The danger with implementing bound constraints in this way (or by Box's method) is that you may collapse the simplex into a lower-dimensional subspace. I'm not aware of a better way, however. In any case, this collapse of the simplex is somewhat ameliorated by restarting, such as when Nelder-Mead is used within the Subplex algorithm below.
Sbplx (based on Subplex)
This is my re-implementation of Tom Rowan's "Subplex" algorithm. As Rowan expressed a preference that other implementations of his algorithm use a different name, I called my implementation "Sbplx" (referred to in NLopt as
Subplex (a variant of Nelder-Mead that uses Nelder-Mead on a sequence of subspaces) is claimed to be much more efficient and robust than the original Nelder-Mead, while retaining the latter's facility with discontinuous objectives, and in my experience these claims seem to be true in many cases. (However, I'm not aware of any proof that Subplex is globally convergent, and perhaps it may fail for some objectives like Nelder-Mead; YMMV.)
I used the description of Rowan's algorithm in his PhD thesis:
- T. Rowan, "Functional Stability Analysis of Numerical Algorithms", Ph.D. thesis, Department of Computer Sciences, University of Texas at Austin, 1990.
I would have preferred to use Rowan's original implementation, posted by him on Netlib:
Unfortunately, the legality of redistributing or modifying this code is unclear, because it lacks anything resembling a license statement. After some friendly emails with Rowan in which he promised to consider providing a clear open-source/free-software license, I lost touch with him and his old email address now seems invalid.
Since the algorithm is not too complicated, however, I just rewrote it. There seem to be slight differences between the behavior of my implementation and his (probably due to different choices of initial subspace and other slight variations, where his paper was ambiguous), but the number of iterations to converge on my test problems seems to be quite close (within ±10% of the number of function evaluations for most problems).
The only major difference between my implementation and Rowan's, as far as I can tell, is that I implemented explicit support for bound constraints (via the method in the Box paper as described above). This seems to be a big improvement in the case where the optimum lies against one of the constraints.
Local gradient-based optimization
Of these algorithms, only MMA and SLSQP support arbitrary nonlinear inequality constraints, and only SLSQP supports nonlinear equality constraints; the rest support bound-constrained or unconstrained problems only. (However, any of them can be applied to nonlinearly constrained problems by combining them with the augmented Lagrangian method below.)
MMA (Method of Moving Asymptotes) and CCSA
My implementation of the globally-convergent method-of-moving-asymptotes (MMA) algorithm for gradient-based local optimization, including nonlinear inequality constraints (but not equality constraints), specified in NLopt as
NLOPT_LD_MMA, as described in:
- Krister Svanberg, "A class of globally convergent optimization methods based on conservative convex separable approximations," SIAM J. Optim. 12 (2), p. 555-573 (2002).
This is an improved CCSA ("conservative convex separable approximation") variant of the original MMA algorithm published by Svanberg in 1987, which has become popular for topology optimization. (Note: "globally convergent" does not mean that this algorithm converges to the global optimum; it means that it is guaranteed to converge to some local minimum from any feasible starting point.)
At each point x, MMA forms a local approximation using the gradient of f and the constraint functions, plus a quadratic "penalty" term to make the approximations "conservative" (upper bounds for the exact functions). The precise approximation MMA forms is difficult to describe in a few words, because it includes nonlinear terms consisting of a poles at some distance from x (outside of the current trust region), almost a kind of Padé approximant. The main point is that the approximation is both convex and separable, making it trivial to solve the approximate optimization by a dual method. Optimizing the approximation leads to a new candidate point x. The objective and constraints are evaluated at the candidate point. If the approximations were indeed conservative (upper bounds for the actual functions at the candidate point), then the process is restarted at the new x. Otherwise, the approximations are made more conservative (by increasing the penalty term) and re-optimized.
(If you contact Professor Svanberg, he has been willing in the past to graciously provide you with his original code, albeit under restrictions on commercial use or redistribution. The MMA implementation in NLopt, however, is completely independent of Svanberg's, whose code we have not examined; any bugs are my own, of course.)
I also implemented another CCSA algorithm from the same paper,
NLOPT_LD_CCSAQ: instead of constructing local MMA approximations, it constructs simple quadratic approximations (or rather, affine approximations plus a quadratic penalty term to stay conservative). This is the ccsa_quadratic code. It seems to have similar convergence rates to MMA for most problems, which is not surprising as they are both essentially similar. However, for the quadratic variant I implemented the possibility of preconditioning: including a user-supplied Hessian approximation in the local model. It is easy to incorporate this into the proof in Svanberg's paper, and to show that global convergence is still guaranteed as long as the user's "Hessian" is positive semidefinite, and it practice it can greatly improve convergence if the preconditioner is a good approximation for the real Hessian (at least for the eigenvectors of the largest eigenvalues).
NLOPT_LD_MMA and
NLOPT_LD_CCSAQ algorithms support the following internal parameters, which can be
specified using the
nlopt_set_param API:
inner_maxeval: If ≥ 0, gives maximum number of "inner" iterations of the algorithm where it tries to ensure that its approximatations are "conservative"; defaults to
0(no limit). It can be useful to specify a finite number (e.g.
10) for this parameter if inaccuracies in your gradient or objective function are preventing the algorithm from making progress.
dual_algorithm(defaults to
dual_ftol_rel(defaults to
dual_ftol_abs(defaults to
dual_xtol_rel(defaults to
dual_xtol_abs(defaults to
dual_maxeval(defaults to
100000): These specify how the algorithm internally solves the "dual" optimization problem for its approximate objective. Because this subsidiary solve requires no evaluations of the user's objective function, it is typically fast enough that we can solve it to high precision without worrying too much about the details. Howeve,r in high-dimensional problems you may notice that MMA/CCSA is taking a long time between optimization steps, in which case you may want to increase
dual_ftol_relor make other changes. If these parameters are not specified, NLopt takes them from the subsidiary-optimizer algorithm if that has been specified, and otherwise uses the defaults indicated here.
verbosity: If > 0, causes the algorithm to print internal status information on each iteration.
Specified in NLopt as
NLOPT_LD_SLSQP, this is a sequential quadratic programming (SQP) algorithm for nonlinearly constrained gradient-based optimization (supporting both inequality and equality constraints), based on the implementation by Dieter Kraft and described in:
- Dieter Kraft, "A software package for sequential quadratic programming", Technical Report DFVLR-FB 88-28, Institut für Dynamik der Flugsysteme, Oberpfaffenhofen, July 1988.
- Dieter Kraft, "Algorithm 733: TOMP–Fortran modules for optimal control calculations," ACM Transactions on Mathematical Software, vol. 20, no. 3, pp. 262-281 (1994).
(I believe that SLSQP stands for something like "Sequential Least-Squares Quadratic Programming," because the problem is treated as a sequence of constrained least-squares problems, but such a least-squares problem is equivalent to a QP.) The algorithm optimizes successive second-order (quadratic/least-squares) approximations of the objective function (via BFGS updates), with first-order (affine) approximations of the constraints.
The Fortran code was obtained from the SciPy project, who are responsible for obtaining permission to distribute it under a free-software (3-clause BSD) license.
The code was modified for inclusion in NLopt by S. G. Johnson in 2010, with the following changes. The code was converted to C and manually cleaned up. It was modified to be re-entrant (preserving the reverse-communication interface but explicitly saving the state in a data structure). The reverse-communication interface was wrapped with an NLopt-style interface, with NLopt stopping conditions. The inexact line search was modified to evaluate the functions including gradients for the first step, since this removes the need to evaluate the function+gradient a second time for the same point in the common case when the inexact line search concludes after a single step; this is motivated by the fact that NLopt's interface combines the function and gradient computations. Since roundoff errors sometimes pushed SLSQP's parameters slightly outside the bound constraints (not allowed by NLopt), we added checks to force the parameters within the bounds. We fixed a bug in the LSEI subroutine (use of uninitialized variables) for the case where the number of equality constraints equals the dimension of the problem. The LSQ subroutine was modified to handle infinite lower/upper bounds (in which case those constraints are omitted).
Note: Because the SLSQP code uses dense-matrix methods (ordinary BFGS, not low-storage BFGS), it requires O(n2) storage and O(n3) time in n dimensions, which makes it less practical for optimizing more than a few thousand parameters.
Low-storage BFGS
This algorithm in NLopt (specified by NLOPT_LD_LBFGS), is based on a Fortran implementation of the low-storage BFGS algorithm written by Prof. Ladislav Luksan, and graciously posted online under the GNU LGPL at:
The original L-BFGS algorithm, based on variable-metric updates via Strang recurrences, was described by the papers:
- J. Nocedal, "Updating quasi-Newton matrices with limited storage," Math. Comput. 35, 773-782 (1980).
- D. C. Liu and J. Nocedal, "On the limited memory BFGS method for large scale optimization," ''Math. Programming' 45, p. 503-528 (1989).
I converted Prof. Luksan's code to C with the help of f2c, and made a few minor modifications (mainly to include the NLopt termination criteria).
One of the parameters of this algorithm is the number M of gradients to "remember" from previous optimization steps: increasing M increases the memory requirements but may speed convergence. NLopt sets M to a heuristic value by default, but this can be changed by the set_vector_storage function.
Preconditioned truncated Newton
This algorithm in NLopt, is based on a Fortran implementation of a preconditioned inexact truncated Newton algorithm written by Prof. Ladislav Luksan, and graciously posted online under the GNU LGPL at:
NLopt includes several variations of this algorithm by Prof. Luksan. First, a variant preconditioned by the low-storage BFGS algorithm with steepest-descent restarting, specified as
NLOPT_LD_TNEWTON_PRECOND_RESTART. Second, simplified versions
NLOPT_LD_TNEWTON_PRECOND (same without restarting),
NLOPT_LD_TNEWTON_RESTART (same without preconditioning), and
NLOPT_LD_TNEWTON (same without restarting or preconditioning).
The algorithms are based on the ones described by:
- R. S. Dembo and T. Steihaug, "Truncated Newton algorithms for large-scale optimization," Math. Programming 26, p. 190-212 (1983) http://doi.org/10.1007/BF02592055.
I converted Prof. Luksan's code to C with the help of f2c, and made a few minor modifications (mainly to include the NLopt termination criteria).
One of the parameters of this algorithm is the number M of gradients to "remember" from previous optimization steps: increasing M increases the memory requirements but may speed convergence. NLopt sets M to a heuristic value by default, but this can be changed by the set_vector_storage function.
Shifted limited-memory variable-metric
This algorithm in NLopt, is based on a Fortran implementation of a shifted limited-memory variable-metric algorithm by Prof. Ladislav Luksan, and graciously posted online under the GNU LGPL at:
There are two variations of this algorithm:
NLOPT_LD_VAR2, using a rank-2 method, and
NLOPT_LD_VAR1, using a rank-1 method.
The algorithms are based on the ones described by:
- J. Vlcek and L. Luksan, "Shifted limited-memory variable metric methods for large-scale unconstrained minimization," J. Computational Appl. Math. 186, p. 365-390 (2006).
I converted Prof. Luksan's code to C with the help of f2c, and made a few minor modifications (mainly to include the NLopt termination criteria).
One of the parameters of this algorithm is the number M of gradients to "remember" from previous optimization steps: increasing M increases the memory requirements but may speed convergence. NLopt sets M to a heuristic value by default, but this can be changed by the set_vector_storage function.
Augmented Lagrangian algorithm
There is one algorithm in NLopt that fits into all of the above categories, depending on what subsidiary optimization algorithm is specified, and that is the augmented Lagrangian method described in:
- Andrew R. Conn, Nicholas I. M. Gould, and Philippe L. Toint, "A globally convergent augmented Lagrangian algorithm for optimization with general constraints and simple bounds," SIAM J. Numer. Anal. vol. 28, no. 2, p. 545-572 (1991).
- E. G. Birgin and J. M. Martínez, "Improving ultimate convergence of an augmented Lagrangian method," Optimization Methods and Software vol. 23, no. 2, p. 177-195 (2008).
This method combines the objective function and the nonlinear inequality/equality constraints (if any) in to a single function: essentially, the objective plus a "penalty" for any violated constraints. This modified objective function is then passed to another optimization algorithm with no nonlinear constraints. If the constraints are violated by the solution of this sub-problem, then the size of the penalties is increased and the process is repeated; eventually, the process must converge to the desired solution (if it exists).
The subsidiary optimization algorithm is specified by the
nlopt_set_local_optimizer function, described in the NLopt Reference. (Don't forget to set a stopping tolerance for this subsidiary optimizer!) Since all of the actual optimization is performed in this subsidiary optimizer, the subsidiary algorithm that you specify determines whether the optimization is gradient-based or derivative-free. In fact, you can even specify a global optimization algorithm for the subsidiary optimizer, in order to perform global nonlinearly constrained optimization (although specifying a good stopping criterion for this subsidiary global optimizer is tricky).
The augmented Lagrangian method is specified in NLopt as
NLOPT_AUGLAG. We also provide a variant,
NLOPT_AUGLAG_EQ, that only uses penalty functions for equality constraints, while inequality constraints are passed through to the subsidiary algorithm to be handled directly; in this case, the subsidiary algorithm must handle inequality constraints (e.g. MMA or COBYLA).
While NLopt uses an independent re-implementation of the Birgin and Martínez algorithm, those authors provide their own free-software implementation of the method as part of the TANGO project, and implementations can also be found in semi-free packages like LANCELOT.


text:
Listen to police and fire departments from around the world on your phone!
Scanner Radio Pro
Listen to live audio from over 3,300 police and fire scanners, weather radios, and amateur radio repeaters from around the world (primarily in the United States and Australia though, with more being added daily).
* Add scanners you listen to the most to your Favorites list for quick access.
* View scanners that are located nearest you, sorted by distance, by clicking on "Near Me"
* View the top 50 scanners that have the most listeners (updated every 5 minutes).
* View list of scanners added most recently (new additions are being added all the time).
* Browse the directory of scanner feeds by location or by genre (public safety, weather, railroad, etc).
* Configure alerts to have the app notify you when lots of people are listening to a scanner (indicating that something big may be happening).
* Add Scanner Radio widgets and/or shortcuts to your phone's home screen for quick access.
* Add a "Scanner Radio Favorite" shortcut to your home screen to launch a scanner feed via an alarm clock app or automation app.
* Allows you to listen to archived audio (from the past 30 days) if you have a RadioReference.com Premium Subscription. Their premium subscription is $15 for 6 months, without it you will not be able to access their audio archives using the app.
In addition to the above features, you also get the following features with this version of the app:
* The ads are removed.
* Allows you to specify what times of day you want to receive listener alerts.
* Allows you to setup listener alerts for scanners located near you.
* The play button at the top of the directory screens and on the widgets is functional.
* Acts as a Tasker Plug-in, allows you to have Tasker launch the app and have one of your Favorites automatically begin playing based on one or more conditions or have the app stop playing. One use for this feature is to have a scanner feed begin playing when your phone connects to a specific Bluetooth device and then have it stop when the connection to that Bluetooth device is no longer present.
The audio is provided by volunteers using real scanner radios. If your area is not available, see the menu in the app for information on how to get it added.
Explanation of why various permissions are needed:
The "Modify global system settings" permission is needed in order for the app to be able to change the device's "Wi-Fi Sleep Policy" to "Never" (but only with your permission). When you run the app, it will check the setting and ask you if you would like for it to be changed to "Never" (if it's set to something else) so that the scanner audio won't be interrupted if the screen turns off while you're listening over Wi-Fi.
The "Phone Calls / Read Phone State" permission is needed by the app so that it can detect when you're placing a phone call (or when one is being received) so that it can automatically stop the streaming of the audio to prevent it from interfering with the call.
The "Fine (GPS) Location" and "Coarse Location" permissions are required so that the app can determine what scanners are located in your area when you click on "Near Me". When you click on "Near Me" the app first attempts to determine your location via the network, if that fails the app then tries to determine your location via GPS.
The "Automatically Start at Boot" permission is required so that a small portion of the app can be started when your phone boots if (and only if) you turn on the listener alert checking feature of the app (that feature is turned off by default).
If the audio repeats or the app stays connected for only a short time, try returning to a directory screen in the app, then select "Settings" from the menu, then "Player settings", and then try changing the "Streaming method" setting.
Follow "Scanner Radio" on Facebook or ScannerRadio on Twitter to be notified about service interruptions, new beta versions, etc.
What's in this version :
- • Metadata (channel information) is now displayed in the "Now Playing" notification when you're listening to a scanner that contains it (can be disabled in settings).
- • Fixed a bug that resulted in the sleep timer still being in effect after time has expired.
- • Removed the need for the ACCESS_WIFI_STATE permission.
- • Fixed a bug which prevented the alert service from stopping sometimes after it finished processing an alert.
- • Additional improvements to the alert service to make it more efficient
Requires Android:1.6 and up
Mirror:APK 6 MB


text:
Stanford University Press Release (2008):
What would you say influenced your voting decisions in the most recent local or national election? Political preferences? A candidate's stance on a particular issue? The repercussions of a proposition on your economic well-being? All these "rational" factors influence voting, and peoples' ability to vote, based on what is best for them, is a hallmark of the democratic process.
But Stanford Graduate School of Business researchers, doctoral graduates Jonah Berger and Marc Meredith, and S. Christian Wheeler, associate professor of marketing, conclude that a much more subtle and arbitrary factor may also play a role—the particular type of polling location in which you happen to vote.
It's hard to imagine that something as innocuous as polling location (e.g., school, church, or fire station) might actually influence voting behavior, but the Stanford researchers have discovered just that. In fact, Wheeler says "the influence of polling location on voting found in our research would be more than enough to change the outcome of a close election." And, as seen in the neck-to-neck 2000 presidential election where Al Gore ultimately lost to George W. Bush after months of vote counting in Florida, election biases such as polling location could play a significant role in the 2008 presidential election. Even at the proposition level, "Voting at a school could increase support for school spending or voting at a church could decrease support for stem cell initiatives," says Wheeler.
Why might something like polling location influence voting behavior? "Environmental cues, such as objects or places, can activate related constructs within individuals and influence the way they behave," says Berger. now an assistant professor of marketing at the Wharton school. "Voting in a school, for example, could activate the part of a person's identity that cares about kids, or norms about taking care of the community. Similarly, voting in a church could activate norms of following church doctrine. Such effects may even occur outside an individual's awareness."
Using data from Arizona's 2000 general election, Berger, Meredith, a visiting lecturer at MIT, and Wheeler discovered that people who voted in schools were more likely to support raising the state sales tax to fund education. The researchers focused on Proposition 301, which proposed raising the state sales tax from 5.0 percent to 5.6 percent to increase education spending. What they found was that voters were more likely to support this initiative if they voted in a school versus other types of polling locations (55.0 percent versus 53.09 percent).
This effect persisted even when the researchers controlled for—or removed the possibility of—other factors such as:
Where voters lived. People who have kids may be pro-education and more likely to live near, and hence vote at, schools; Political views. Those who voted for Gore or positively on other propositions; and Demographics including age, sex, etc.
In regards to the first control, for example, people were still more likely to support Proposition 301 if they had voted in schools than if they had voted in places that were not schools but had schools nearby. No matter how they cut and spliced the data, the researchers found that voters in schools were more likely to support Proposition 301.
"We want factors like political views—whether someone thinks a candidate is going to make our country a better place—to sway elections," said Berger. "But in forming election policy, we also want to make sure that arbitrary factors such as polling location don't ultimately influence voting behaviors."
To further test their hypothesis, the researchers even conducted the same analysis for the other 13 propositions on the Arizona ballot. They reasoned that if voters who cast their ballots in schools were more likely to vote positively for other unrelated propositions on wildlife or property taxes, for example, then the researchers would know that their model was not adequately accounting for some other factor beyond polling location, and that something such as voting preferences was having an effect. But such additional testing only supported the researchers' hypotheses further.
The researchers also followed up with a lab experiment that allowed for random assignment of voters to pictures of different voting environments that the researchers thought might influence voting behavior. Participants were shown 10 images from well-maintained schools (e.g. lockers, classrooms) or churches (e.g. pews, alters), plus five additional filler images of generic buildings. A control group was shown images of generic buildings.
The participants then voted on a number of initiatives including California's 2004 stem cell funding initiative, Arizona's education initiative, and several others. Initiative wording was taken right from each state's legislative council documents. As predicted by Berger, Meredith, and Wheeler: Environmental cues contained in the photos influenced voting.
Results from the second study showed that participants were less likely to support the stem cell initiative if they were shown church images than if they were shown school images or a generic photo of a building. The subjects also were more likely to support the education initiative if they were shown school images versus church or generic building images. The results further demonstrated that environmental cues present in different polling locations can influence voting outcomes, even when voters are randomly assigned to different environmental cue conditions.
"What our research suggests is that it might be useful to further investigate influences such as polling location to better understand how such factors affect different types of voting situations. From a policy perspective, the hope is that a voting location assignment could be less arbitrary and more determined in order to avoid undue biases in the future," says Wheeler.
(pdf here.)
From USA Today (2012):
University of Maine psychology professor Jordan LaBouff and co-author Wade Rowatt, Ph.D., associate professor of psychology and neuroscience at Baylor, have a new paper out in the International Journal for the Psychology of Religion, finding that people expressed "cold" rather than "warm" attitudes toward gay men and women if they were asked their views while they were within sight of a church.
The research, conducted in England and the Netherlands with participants of 20 different nationalities, found that the unmentioned but evident visual cue of a church prompted people to express more conservative views on a range of issues — foreign aid, immigration, protection of the environment, separation of church and state, and more.
LaBouff said Thursday, "The effect is not specific to Christianity, but the sight of a church highlights our internal boundaries — who is like us and who is not like us. And we are more negative toward people who are not like us, whether we are religious or not."
Related Situationist posts:
- The Informational Situation of Voters
- Reporting Social Facts vs. Pining for Jim Crow: No Comparison Between Reid and Lott
- Racial Attitudes in the Presidential Race
- The Situation of Pollworkers and Voting Booths – Abstract
- The Racial Situation of Voting
- The Interior Situation of Undecided Voters
- On Being a Mindful Voter
- Implicit Associations in the 2008 Presidential Election
- The Situation of Political Animals
- Your Brain on Politics.


text:
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